Group Decision-Making on an Optimal Stopping Problem

Michael D. Lee, Michael J. Paradowski
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Abstract

We consider group decision-making on an optimal stopping problem, for which large and stable individual differences have previously been established. In the problem, people are presented with a sequence of five random numbers between 0 and 100, one at a time, and are required to choose the maximum of the sequence, without being al- lowed to return to earlier values in the sequence. We examine group decision-making on these problems in an experimental setting where group members are isolated from one another, and interact solely via networked computers. The group members register their initial accept or reject decision for each value in the sequence, and then provide a potentially revised decision having viewed the recommendations of the other group members. Group decisions are made according to one of three conditions, requiring either consensus to accept from all group members, a majority of accept decisions from the group, or the acceptance of an appointed group leader. We compare individual decision-making to group decision-making under these three conditions, and find that, under some conditions, groups often significantly outperform even their best members. Using a signal detection analysis we provide an account of how the group decision- making conditions differ from one another, and from individual decision-making. Key findings are that people do not often revise their decisions, but, in the consensus and leadership conditions, are more conservative in their initial decisions. This conservatism removes the individual bias towards choosing values too early in the sequence, allowing the groups to perform better than their individual members. In the majority condition, however, people continue to behave as they did individually, and the group shows the same bias in decision-making.
一类最优停车问题的群体决策
我们考虑了一个最优停车问题的群体决策,对于这个问题,以前已经建立了大而稳定的个体差异。在这个问题中,向人们展示一个由0到100之间的五个随机数组成的序列,每次一个,并要求他们选择该序列的最大值,而不允许返回到序列中较早的值。我们在实验环境中研究这些问题的群体决策,在实验环境中,群体成员彼此隔离,仅通过网络计算机进行交互。组成员为序列中的每个值注册他们的初始接受或拒绝决策,然后在查看了其他组成员的建议后提供一个可能经过修改的决策。群体决策是根据以下三个条件之一做出的,要么要求所有群体成员达成共识,要么要求大多数人接受群体的决策,要么要求接受指定的群体领导。在这三种情况下,我们将个人决策与群体决策进行比较,发现在某些情况下,群体的表现往往明显优于他们最优秀的成员。使用信号检测分析,我们提供了群体决策条件如何彼此不同,以及与个人决策不同的说明。主要发现是,人们不经常修改他们的决定,但是,在共识和领导条件下,他们在最初的决定中更加保守。这种保守性消除了在序列中过早选择值的个人偏见,使群体比其个人成员表现得更好。然而,在大多数情况下,人们继续表现得像他们个人一样,群体在决策时表现出同样的偏见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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